

'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase      					=     logging.get_logger(__name__)

_lowerCamelCase      					=     {
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}
class 					_snake_case		(__SCREAMING_SNAKE_CASE):
			__A  :	str        ="xmod"






			def __init__(  self			,_snake_case=3_05_22			,_snake_case=7_68			,_snake_case=12			,_snake_case=12			,_snake_case=30_72			,_snake_case="gelu"			,_snake_case=0.1			,_snake_case=0.1			,_snake_case=5_12			,_snake_case=2			,_snake_case=0.02			,_snake_case=1E-12			,_snake_case=1			,_snake_case=0			,_snake_case=2			,_snake_case="absolute"			,_snake_case=True			,_snake_case=None			,_snake_case=False			,_snake_case=2			,_snake_case=False			,_snake_case=True			,_snake_case=True			,_snake_case=("en_XX",)			,_snake_case=None			,**_snake_case			,):
				super().__init__(pad_token_id=_snake_case			,bos_token_id=_snake_case			,eos_token_id=_snake_case			,**_snake_case     )

				UpperCAmelCase_     :      Tuple						=  vocab_size
				UpperCAmelCase_     :      str						=  hidden_size
				UpperCAmelCase_     :      List[Any]						=  num_hidden_layers
				UpperCAmelCase_     :      List[Any]						=  num_attention_heads
				UpperCAmelCase_     :      List[str]						=  hidden_act
				UpperCAmelCase_     :      Dict						=  intermediate_size
				UpperCAmelCase_     :      Dict						=  hidden_dropout_prob
				UpperCAmelCase_     :      Union[str, Any]						=  attention_probs_dropout_prob
				UpperCAmelCase_     :      int						=  max_position_embeddings
				UpperCAmelCase_     :      Optional[Any]						=  type_vocab_size
				UpperCAmelCase_     :      Any						=  initializer_range
				UpperCAmelCase_     :      Optional[Any]						=  layer_norm_eps
				UpperCAmelCase_     :      Any						=  position_embedding_type
				UpperCAmelCase_     :      Union[str, Any]						=  use_cache
				UpperCAmelCase_     :      Union[str, Any]						=  classifier_dropout
				UpperCAmelCase_     :      Optional[Any]						=  pre_norm
				UpperCAmelCase_     :      int						=  adapter_reduction_factor
				UpperCAmelCase_     :      Dict						=  adapter_layer_norm
				UpperCAmelCase_     :      str						=  adapter_reuse_layer_norm
				UpperCAmelCase_     :      Dict						=  ln_before_adapter
				UpperCAmelCase_     :      List[Any]						=  list(_snake_case     )
				UpperCAmelCase_     :      Optional[Any]						=  default_language




class 					_snake_case		(__SCREAMING_SNAKE_CASE):






			@property
			def 		UpperCamelCase__							(  self     ):
				if self.task == "multiple-choice":
					UpperCAmelCase_     :      Any						=  {0: "batch", 1: "choice", 2: "sequence"}
				else:
					UpperCAmelCase_     :      Optional[Any]						=  {0: "batch", 1: "sequence"}
				return OrderedDict(
				    [
				        ("input_ids", dynamic_axis),
				        ("attention_mask", dynamic_axis),
				    ]     )






"""simple docstring"""



import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


a       :						int       		=		'''scheduler_config.json'''




class 		a_    (			_UpperCAmelCase						):
    a   :					List[Any]			     =					1
    a   :					Tuple			     =					2
    a   :					Dict			     =					3
    a   :					str			     =					4
    a   :					Optional[int]			     =					5
    a   :					Any			     =					6
    a   :					int			     =					7
    a   :					Any			     =					8
    a   :					List[Any]			     =					9
    a   :					Any			     =					10
    a   :					List[str]			     =					11
    a   :					Optional[int]			     =					12
    a   :					Any			     =					13
    a   :					Dict			     =					14







@dataclass
class 		a_    (			_UpperCAmelCase						):
    a   :					torch.FloatTensor







class 		a_    :
    a   :					Dict			     =					SCHEDULER_CONFIG_NAME
    a   :					List[str]			     =					[]
    a   :					Optional[int]			     =					True







    @classmethod
    def   _snake_case       (      cls      :							List[str]  ,       __UpperCamelCase      :							Dict[str, Any] = None  ,       __UpperCamelCase      :							Optional[str] = None  ,       __UpperCamelCase      :							List[str]=False  ,       **__UpperCamelCase      :							int  ,       )		->Dict:






        '''simple docstring'''






        _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase        = cls.load_config(
            pretrained_model_name_or_path=__UpperCamelCase  ,       subfolder=__UpperCamelCase  ,       return_unused_kwargs=__UpperCamelCase  ,       return_commit_hash=__UpperCamelCase  ,       **__UpperCamelCase  ,       )
        return cls.from_config(__UpperCamelCase  ,       return_unused_kwargs=__UpperCamelCase  ,       **__UpperCamelCase  )







    def   _snake_case       (      self      :							Tuple  ,       __UpperCamelCase      :							Union[str, os.PathLike]  ,       __UpperCamelCase      :							bool = False  ,       **__UpperCamelCase      :							List[str]  )		->Any:






        '''simple docstring'''






        self.save_config(save_directory=__UpperCamelCase  ,       push_to_hub=__UpperCamelCase  ,       **__UpperCamelCase  )







    @property
    def   _snake_case       (      self      :							Optional[int]  )		->List[Any]:






        '''simple docstring'''






        return self._get_compatibles()







    @classmethod
    def   _snake_case       (      cls      :							List[str]  )		->Dict:






        '''simple docstring'''






        _UpperCAmelCase        = list(set([cls.__name__] + cls._compatibles  )  )
        _UpperCAmelCase        = importlib.import_module(__name__.split("""."""  )[0]  )
        _UpperCAmelCase        = [
            getattr(__UpperCamelCase  ,       __UpperCamelCase  ) for c in compatible_classes_str if hasattr(__UpperCamelCase  ,       __UpperCamelCase  )
        ]
        return compatible_classes